Maximum Likelihood Estimation of the Markov-Switching GARCH Model Based on a General Collapsing Procedure

The final publication is available at Springer - Methodology and Computing in Applied Probability (DOI: 10.1007/s11009-016-9541-4)

33 Pages Posted: 11 Dec 2013 Last revised: 3 Jan 2017

See all articles by Maciej Augustyniak

Maciej Augustyniak

University of Montreal - Department of Mathematics and Statistics

Mathieu Boudreault

University of Quebec at Montreal (UQAM)

Manuel Morales

University of Montreal

Date Written: January 2, 2017

Abstract

The Markov-switching GARCH model allows for a GARCH structure with time-varying parameters. This flexibility is unfortunately undermined by a path dependence problem which complicates the parameter estimation process. This problem led to the development of computationally intensive estimation methods and to simpler techniques based on an approximation of the model, known as collapsing procedures. This article develops an original algorithm to conduct maximum likelihood inference in the Markov-switching GARCH model, generalizing and improving previously proposed collapsing approaches. A new relationship between particle filtering and collapsing procedures is established which reveals that this algorithm corresponds to a deterministic particle filter. Simulation and empirical studies show that the proposed method allows for a fast and accurate estimation of the model.

Keywords: Markov-switching, regime-switching, GARCH, particle filtering, path dependence, collapsing

JEL Classification: C13, C51, C63

Suggested Citation

Augustyniak, Maciej and Boudreault, Mathieu and Morales, Manuel, Maximum Likelihood Estimation of the Markov-Switching GARCH Model Based on a General Collapsing Procedure (January 2, 2017). The final publication is available at Springer - Methodology and Computing in Applied Probability (DOI: 10.1007/s11009-016-9541-4). Available at SSRN: https://ssrn.com/abstract=2365763 or http://dx.doi.org/10.2139/ssrn.2365763

Maciej Augustyniak (Contact Author)

University of Montreal - Department of Mathematics and Statistics ( email )

C.P. 6128, succursale Centre-ville
Montreal, Quebec H3C 3J7
Canada

HOME PAGE: http://dms.umontreal.ca/

Mathieu Boudreault

University of Quebec at Montreal (UQAM) ( email )

PB 8888 Station DownTown
Succursale Centre Ville
Montreal, Quebec H3C3P8
Canada

Manuel Morales

University of Montreal ( email )

C.P. 6128 succursale Centre-ville
Montreal, Quebec H3C 3J7
Canada

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